• Management & Information Systems Review
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• v.34 no.3
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• pp.251-271
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• 2015

This article examines the HRD implications of using robotic technology in the workplace. Because existing literature has been primarily about the technical engineering aspects of robotics, it is difficult to understand the socio-cultural perspective about the challenges and potentials of robotization in the workplace. Especially, in order to identify the best organizational support appropriate for working with robots, this article indicates alternative perspective for observing human-robot interaction in the workplace. In addition, this article points out four implications of robotic technology in organizations for practice and research development in HRD. These implications were identified as (1) defining the components of expertise in terms of human-robot interaction, (2) coping with organizational change process resulting from robotic technology, (3) designing appropriate interventions for an organization to effectively assist human-robot interaction, and (4) establishing the code of work ethics in the robotic age. The suggested implications can contribute to shaping conceptual frameworks for further empirical social science research.

• Journal of Korean Academy of Nursing
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• v.53 no.1
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• pp.55-68
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• 2023

Purpose: The purpose of this study was to identify the main keywords, network properties, and main topics of news articles related to artificial intelligence technology in the field of nursing. Methods: After collecting artificial intelligence-and nursing-related news articles published between January 1, 1991, and July 24, 2022, keywords were extracted via preprocessing. A total of 3,267 articles were searched, and 2,996 were used for the final analysis. Text network analysis and topic modeling were performed using NetMiner 4.4. Results: As a result of analyzing the frequency of appearance, the keywords used most frequently were education, medical robot, telecom, dementia, and the older adults living alone. Keyword network analysis revealed the following results: a density of 0.002, an average degree of 8.79, and an average distance of 2.43; the central keywords identified were 'education,' 'medical robot,' and 'fourth industry.' Five topics were derived from news articles related to artificial intelligence and nursing: 'Artificial intelligence nursing research and development in the health and medical field,' 'Education using artificial intelligence for children and youth care,' 'Nursing robot for older adults care,' 'Community care policy and artificial intelligence,' and 'Smart care technology in an aging society.' Conclusion: The use of artificial intelligence may be helpful among the local community, older adult, children, and adolescents. In particular, health management using artificial intelligence is indispensable now that we are facing a super-aging society. In the future, studies on nursing intervention and development of nursing programs using artificial intelligence should be conducted.

• Science of Emotion and Sensibility
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• v.11 no.4
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• pp.629-636
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• 2008

In recent years, a large number of robots have been developed in several countries, and these robots have been built for the purpose to appeal to users by well designed human-robot interaction. In case of the robots developed so far, they show proper reactions only when there is a certain input. On the other hands, they cannot perform in a standby mode which means there is no input. In other words, if a robot does not make any motion in standby mode, users may feel that the robot is being turned-off or even out of work. Especially, the social service robots maintain the standby status after finishing a certain task. In this period of time, if the robots can make human-like behavioral patterns such like a person in help desk, then they are expected to make people feels that they are alive and is more likely to interact with them. It is said that even if there is no interaction with others or the environment, people normally reacts to internal or external stimuli which are created by themselves such as moving their eyes or bodies. In order to create robotic behavioral patterns for standby mode, we analyze the actual facial expression and behavior from people who are in neutral affective emotion based on ethnographic methodology and apply extracted characteristics to our robots. Moreover, by using the robots which can show those series of expression and action, our research needs to find that people can feel like they are alive.

• Journal of IKEEE
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• v.23 no.4
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• pp.1440-1447
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• 2019

Currently, the prevalence of autism spectrum disorders in children is reported to be higher and shows various types of disorders. In particular, they are having difficulty in communication due to communication impairment in the area of social communication and need to be improved through training. Thus, this study proposes a method of acquiring voice information through a microphone mounted on a robot designed through preliminary research and using this information to make intelligent motions. An ANN(Artificial Neural Network) was used to classify the speech data into robot motions, and we tried to improve the accuracy by combining the Recurrent Neural Network based on Convolutional Neural Network. The preprocessing of input speech data was analyzed using MFCC(Mel-Frequency Cepstral Coefficient), and the motion of the robot was estimated using various data normalization and neural network optimization techniques. In addition, the designed ANN showed a high accuracy by conducting an experiment comparing the accuracy with the existing architecture and the method of human intervention. In order to design robot motions with higher accuracy in the future and to apply them in the treatment and education environment of children with autism.

• Science of Emotion and Sensibility
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• v.26 no.3
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• pp.29-40
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• 2023

The term and concept of "immortality" has garnered a considerable amount of attention worldwide. However, research on this topic is lacking, and the question of when the mind of a deceased individual survives death has yet to be answered. This research investigates whether morality and mind perception of the dead correlate with immortality. Study 1 measures the perceived immortality of people, who were good or evil in life. The results show that the perceived morality is related with the perceived immortality. Moreover, participants indicated the extent to which each person had maintained a degree of morality and agency/experience of the mind. Therefore, morality and mind perception toward a person are related to perceived immortality. In Study 2, participants were asked to read three essays on robots (good, evil, and nonmoral), and had to indicate the extent to which each robot maintains a degree of immortality, morality, and agency/experience of the mind. The results show that good spirits of a robot are related to higher scores of mind perception toward the robot, resulting in increasing tendency of perceived immortality. These results provide implications that the morality of humans and robots can mediate the relationship between mind perception and immortality. This work extends on previous research on the determinants of social robots for overcoming difficulties in human-robot interaction.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.185-209
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• 2023

With the advent of the 4th industrial revolution, various technologies have received much attention. Technologies related to the 4th industry include the Internet of Things (IoT), big data, artificial intelligence, virtual reality (VR), 3D printers, and robotics, and these technologies are often converged. In particular, the robotics field is combined with technologies such as big data, artificial intelligence, VR, and digital twins. Accordingly, much research using robotics is being conducted, which is applied to distribution, airports, hotels, restaurants, and transportation fields. In the given situation, research on human-robot interaction is attracting attention, but it has not yet reached the level of user satisfaction. However, research on robots capable of perfect communication is steadily being conducted, and it is expected that it will be able to replace human emotional labor. Therefore, it is necessary to discuss whether the current human-robot interaction technology can be applied to business. To this end, this study first examines the trend of human-robot interaction technology. Second, we compare LDA (Latent Dirichlet Allocation) topic modeling and BERTopic topic modeling methods. As a result, we found that the concept of human-robot interaction and basic interaction was discussed in the studies from 1992 to 2002. From 2003 to 2012, many studies on social expression were conducted, and studies related to judgment such as face detection and recognition were conducted. In the studies from 2013 to 2022, service topics such as elderly nursing, education, and autism treatment appeared, and research on social expression continued. However, it seems that it has not yet reached the level that can be applied to business. As a result of comparing LDA (Latent Dirichlet Allocation) topic modeling and the BERTopic topic modeling method, it was confirmed that BERTopic is a superior method to LDA.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.135-146
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• 2019

This study was designed to analyze trends in the entire convergence research beyond academic research through social media big data analysis at a time when interdisciplinary convergence research is emphasized along with the fourth industrial revolution. For this purpose, about 150,000 cases of texts and titles were acquired for about 10 years from January 2009 to September 2018 in connection with the convergence research in social media, and word cloud and network analysis were conducted. As a results, the research fields that were actively conducted for each period were eco-tech in 2009 and 2010, smart technology in 2011 and 2012, information and communication in 2013 and 2014, robots in 2015 and 2016, and artificial intelligence in 2017 and 2018. Also, the research areas that have been consistently conducted for about 10 years are culture, design, chemistry, nanotechnology, biotechnology, robot, IT, and information and communication. Since this study identifies trends in convergence research over time, it can be helpful to researchers who are planning convergence research direction by understanding the trends of convergence research.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.1-9
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• 2022

Today, artificial intelligence (AI) has emerged as a key driver of national competitiveness, but it is also causing unexpected side effects in society. This study intends to examine major social issues by collecting papers on AI targeting KCI journals in the field of social science. Therefore, we conducted keyword analysis of papers from 2016 to 2020. As a result of the analysis, the keywords for 'robot' and 'education' appeared the most, and the top six clusters (issues) were derived through the keyword network. The main issues are as follows: the background and/or basic concept of AI, AI education, side effects of AI, legal issues of AI-based creations, intention to use AI products/services, and AI ethics. The results of this study can be used to expand the discussion on the social aspects of AI and to find policy directions at the national level.

• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1125-1133
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• 2014

Recently, there are many researches have been studying for analyzing user interests and emotions based on users profiles and diverse information from Social Network Services (SNSs) due to their popularities. However, most of traditional researches are focusing on their researches based on single resource such as text, image, hash tag, and more, in order to obtain what user emotions are. Hence, this paper propose a method for obtaining user emotional information by analyzing texts and images both from Instagram which is one of the well-known image based SNSs. In order to extract emotional information from given images, we firstly apply GRAB-CUT algorithm to retrieve objects from given images. These retrieved objects will be regenerated by their representative colors, and compared with emotional vocabulary table for extracting which vocabularies are the most appropriate for the given images. Afterward, we will extract emotional vocabularies from text information in the comments for the given images, based on frequencies of adjective words. Finally, we will measure WUP similarities between adjective words and emotional words which extracted from the previous step. We believe that it is possible to obtain more precise user emotional information if we analyzed images and texts both time.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1391-1399
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• 2015

In recent times, studies sentiment analysis are being actively conducted by implementing natural language processing technologies for analyzing subjective data such as opinions and attitudes of users expressed on the Web, blogs, and social networking services (SNSs). Conventionally, to classify the sentiments in texts, most studies determine positive/negative/neutral sentiments by assigning polarity values for sentiment vocabulary using sentiment lexicons. However, in this study, sentiments are classified based on Thayer's model, which is psychologically defined, unlike the polarity classification used in opinion mining. In this paper, as a method for classifying the sentiments, sentiment categories are proposed by extracting sentiment keywords for major sentiments by using hashtags, which are essential elements of Instagram. By applying sentiment categories to user posts, sentiments can be determined through the similarity measurement between the sentiment adjective candidates and the sentiment keywords. The test results of the proposed method show that the average accuracy rate for all the sentiment categories was 90.7%, which indicates good performance. If a sentiment classification system with a large capacity is prepared using the proposed method, then it is expected that sentiment analysis in various fields will be possible, such as for determining social phenomena through SNS.